Blended Learning: Examining Must-Have, Hybrid, and Value-Added Quality Attributes of Hospitality and Tourism Education

(1)

Full Terms & Conditions of access and use can be found at

https://www.tandfonline.com/action/journalInformation?journalCode=uhat20

Journal of Hospitality & Tourism Education

ISSN: (Print) (Online) Journal homepage: https://www.tandfonline.com/loi/uhat20

Blended Learning: Examining Must-Have, Hybrid, and Value-Added Quality Attributes of Hospitality and Tourism Education

Supawat Meeprom & Pipatpong Fakfare

To cite this article: Supawat Meeprom & Pipatpong Fakfare (2023): Blended Learning:

Examining Must-Have, Hybrid, and Value-Added Quality Attributes of Hospitality and Tourism Education, Journal of Hospitality & Tourism Education, DOI: 10.1080/10963758.2023.2172419 To link to this article: https://doi.org/10.1080/10963758.2023.2172419

Published online: 26 Jan 2023.

Submit your article to this journal

Article views: 74

View related articles

View Crossmark data

(2)

Blended Learning: Examining Must-Have, Hybrid, and Value-Added Quality Attributes of Hospitality and Tourism Education

Supawat Meeprom, PhD ^aand Pipatpong Fakfare, D.HTM ^b

aHospitality and Event Department, Faculty of Business Administration and Accountancy, Khon Kaen University (Thailand); ^bSchool of Humanities and Tourism Management, Bangkok University

ABSTRACT

This paper explores the asymmetric impact of hybrid learning attributes on satisfaction to discover which features are more sensitive to the dissatisfaction, satisfaction, and delight of students. An online survey (n = 647) was conducted using snowball and convenience sampling. By implement- ing impact range performance and asymmetry analyses, the differential effects of hybrid learning attributes (must-have, hybrid, and value-added) on student satisfaction were identified.

Considering the limited knowledge regarding the quality attributes of hybrid learning in the extant hospitality and tourism literature, this research offers understanding as to the dynamic nature of hybrid learning attributes on student satisfaction rather than just identifying quality dimensions.

The results suggest that there are multiple attributes related to the hybrid learning environment (student support, innovative program, industry involvement, program reputation, hybrid learning support and safety measures, and protection) that produce distinctive impacts on satisfaction.

KEYWORDS

Hybrid learning; quality attributes; education;

asymmetric impact;

classroom; satisfaction

Introduction

Hospitality and tourism are among the most important industries as they create meaningful employment opportunities, therefore contributing to the economic improvement of many destinations (Tuna & Basdal, 2021). With the dynamic development of tourism over the past decades, scholars and practitioners have increasingly paid attention to this sector (Fakfare et al., 2020a, 2020b). The demand for hospitality and tourism management education has also increased (M.J. Lee et al., 2019). Thus, many educational institutions worldwide have developed and advanced their hospitality and tourism curricula to cater to the demands anticipated from both students and the industry. According to Griffin (2022), the hospitality and tourism sector is a labor-intensive industry, requiring skilled employees to deliver, operate, and maintain tourism products and services. To develop a highly qualified workforce, higher education is important because the hospitality and tourism sector is heavily reliant on young workers skilled in these areas (Li & Liu, 2016).

Unsurprisingly, the continued development of hospitality and tourism education has been documented in a variety of studies in that area. The extant research generally covers skill and competency requirements for a hospitality and tourism career (Jiang & Aexakis, 2017),

the evaluation and development of hospitality and tourism curriculum (Horng et al., 2019; Ramis, 2021; Tuna &

Basdal, 2021; Yusuf et al., 2018), student internships (Qu et al., 2021; Ramaprasad et al., 2021; Zopiatis et al., 2021), the application of technology in education (Ali et al., 2016;

Qiu et al., 2021; Tolkach & Pratt, 2021), and learning experience/engagement (Gao et al., 2020; Yildiz, 2021).

More recently, due to the emergence of COVID-19, hospitality and tourism education research has covered student satisfaction and delivery methods during the pandemic (Cheng & Agyeiwaah, 2021; Choi et al., 2021;

Tavitiyaman et al., 2021).

According to Zapata-Cuervo et al. (2021), “hybrid learning” (also known as “blended learning”) refers to an instructional delivery approach that integrates online learning with a traditional face-to-face classroom through a platform that combines an application- and/or web- based technique for teaching/coaching. Traditionally, hybrid learning has been generally seen as an innovative teaching method that comprises classwork supplemented by online activity or an extra activity facilitated by the blend of different styles of learning or modes of delivery (Pang et al., 2010). Instructors typically mix online technology with face-to-face teaching practices, thereby enhancing the learning experience of students (Choi et al., 2021). Recently, during the COVID-19 pandemic,

CONTACT Pipatpong Fakfare, D.HTM [email protected] School of Humanities and Tourism Management, Bangkok University, 9/1 Moo 5 Phaholyothin Road, Klong Luang 12120, Thailand.

https://doi.org/10.1080/10963758.2023.2172419

(3)

hybrid learning has become increasingly popular among educational institutions and is considered the best available instructional delivery choice under social distancing and quarantine policies. Many institutions worldwide have offered hybrid courses using a mix of synchronous and asynchronous content (e.g., live synchronous lessons and asynchronous instructional materials with flexible learning hours) to overcome the challenges of teaching and to provide opportunities for students to maintain their hands-on learning experiences during the pandemic (Baker, 2021).

Although the ongoing COVID-19 pandemic has globally caused a serious disruption for hospitality and tourism education, this situation has driven the development of distance learning methods and technologies at a quick pace (S.H. Lee & Deale, 2021). Scholars have also paid more attention to the topic of hybrid learning.

For example, Lei and So (2021) examined the online teaching and learning experiences of university instructors and students in hospitality and tourism programmes. The results showed that these experiences were influenced by different factors, such as the technology, perceived benefits of the hybrid course, instructor’s and student’s technical skills, class interaction and com- munication, the stress caused by COVID-19, and the sudden change from traditional to virtual learning.

Zapata-Cuervo et al. (2021) further explored students’

psychological perceptions of a hybrid learning experience and what factors affected their online class engagement. The findings revealed that students’ self-efficacy and anxiety significantly influenced their online class engagement and, in turn, affected their learning experience. Another recent study by Orlowski et al. (2021) discovered that in the context of online culinary and beverage labs, social presence significantly affects students’ experiential satisfaction through emotional cog- nitive engagement. Surprisingly, the instructors were found to be the main actors that shaped the hybrid learning experience, rather than a student’s peers.

Although previous hospitality and tourism studies have examined the quality attributes of education, scholars have tended to place less attention on the specific quality attributes of hybrid learning. Empirical studies that identify multidimensional quality attributes of hybrid learning, particularly during the pandemic, have been overlooked in the hospitality and tourism education literature (Lei & So, 2021; M.J. Lee et al., 2019), albeit quality attributes are partially depicted and incon- sistent in the extant studies. Moreover, scholars typically overlook asymmetric impacts when evaluating the relationships between hospitality and tourism education quality and classroom satisfaction. This asymmetric impact refers to the dynamic influence of quality

attributes on satisfaction based on three dimensions;

the effect of attributes on satisfaction differs among the categorizations of these attributes – satisfiers, hybrid, and dissatisfiers (Fakfare et al., 2021; Lee et al., 2020).

In the previous literature, it can be observed that linear symmetrical relationships have largely been employed. However, overlooking the asymmetry of hybrid learning attributes on satisfaction inhibits insight into attributes that have superior/inferior impacts on satisfaction/dissatisfaction (J. S. Lee & Choi, 2020). For instance, access to an online library may not make students satisfied, because they take it for granted.

Nevertheless, if an online library is not accessible, students may become very upset. From this perspective, we can see that insight into asymmetric relationships allows the prioritization of hybrid learning quality attributes for an effective arrangement of hybrid learning. Given the measures to limit the spread of COVID-19 in several countries, including Thailand, educational institutions have had a limited range of options for offering distance learning. These include 100% virtual learning, on- demand learning, and a combination of online and on- campus learning, depending on the specific situation in which each institution finds itself (Bangkok Post, 2022).

Considering that flexible models of hybrid learning allow continuous adaptation to “new normal” circum- stances, this study primarily focused on the hybrid por- tion of courses offered by hospitality and tourism programmes during the pandemic. Through the identification of hybrid learning attributes, the purposes of this research were twofold:

(1) To explore the asymmetric impacts of hybrid learning attributes.

(2) To prioritize hybrid learning attributes based on a 3D model (must-have, hybrid, and value-added attributes).

Literature Review

Hospitality and Tourism Education and Hybrid Learning Quality Attributes

Over the past few decades, hospitality and tourism education has progressively developed as the tourism industry has become the largest and fastest growing economic sector in the world (Baker & Magnini, 2016; Fakfare et al., 2022). Nevertheless, given that today’s students are from more diverse backgrounds and cultures than in the past, they likely also have different expectations, prefer- ences, and perceptions toward hospitality and tourism pedagogy (Hsu, 2018). Although multiple modes of learning have been previously established by some tourism

(4)

institutions (Pang et al., 2010), adoption by tourism educators requires specific skills, action plans, and delivery platforms, thereby decelerating the implementation of hybrid courses among educators (Baker, 2021).

According to Hsu (2018), traditional online learning was initially developed to cater to the demands of students who could not attend classes on campus and concentrated on providing asynchronous materials. While asynchronous learning can be delivered at any time and to different locations (particularly, for each unique student), synchronous learning is arranged so that learners communicate with instructors at the same time and can occur either in a physical location (such as on a campus) or online, facilitated by a digital conference platform (such as Zoom, Microsoft Teams, and Google Meet;

Petronzi & Petronzi, 2020). Since the emergence of COVID-19, educational institutions have been increasingly offering both synchronous and asynchronous blended content to facilitate students’ self-learning as well as their classroom interaction. Considering the current situation, it is critical to assess whether hybrid learning education maintains the same quality as in-person learning. Learners have not been given many options regarding the learning modes they prefer (Baker, 2021).

Therefore, it is important to understand critical aspects of hybrid learning attributes in order to continue to offer effective hospitality and tourism programmes, particularly during/after the current pandemic.

In hospitality and tourism education, hybrid learning has been developed and implemented for over a decade.

For example, Pang et al. (2010) investigated whether hospitality and tourism education could respond to the changing demands of the tourism industry. They transformed a programme and developed hybrid learning that integrated collaborative online tools and conventional classroom activities to better engage and motivate students. Gao et al. (2020) explored the influence of a hybrid classroom and student engagement on satisfaction in a hospitality and tourism management course.

Recently, Zapata-Cuervo et al. (2021) examined the impact of students’ psychological perceptions of online learning engagement. Learners assess the quality of hospitality and tourism education by evaluating programme performance through learning platforms and class delivery methods (Choi et al., 2021; Gao et al., 2020).

A student’s quality perception of a hospitality and tourism programme is generally dependent on the performance of learning attributes under the arrangement/

management of an educational institution.

Earlier research has generally concentrated on aggre- gating and verifying quality attributes from a narrow perspective, which differs among studies (M.J. Lee et al., 2019). For example, M. Lee et al. (2016) proposed five

factors of hospitality education programme quality:

learning environment, student support, programme credentials, industry networking, and innovative programmes. Li and Liu (2016) attempted to assess the quality of hospitality and tourism education by taking into account a creative atmosphere. M.J. Lee et al. (2019) further applied dimensions, such as student support, programme credentials, industry networking, and innovative programmes, to examine students’ perceptions of education quality in the US and compare student perceptions between domestic and international groups. Since the emergence of the COVID-19 virus, online class delivery methods and modern technologies have become more important elements in the assessment of education programme quality and the promotion of public safety (Choi et al., 2021). There are also many elements that can influence the success of synchronous and asynchronous learning, particularly related to the learning activities held during/after the COVID-19 pandemic. Many of the previous studies have largely concentrated on teaching design and delivery techniques (Li et al., 2020).

Although previous research serves as a useful foundation for understanding hybrid learning in the field of hospitality and tourism, the attributes of hybrid learning, particularly as it was practiced during/after the COVID-19 pandemic, have not been rigorously developed and validated in the extant literature. A comprehensive understanding of hybrid learning attributes that affect the learning experience of students and, thus, the attractive- ness/effectiveness of a study programme is important to hospitality and tourism education studies. To fill this gap, this study first conducted an analysis of possible dimensions based on the existing hospitality and tourism education literature. This included the domains of the hybrid learning environment, student support, innovative programme, industry involvement, programme reputation, and hybrid learning support (Bailey & Morais, 2005;

Choi et al., 2021; Gao et al., 2020; Li & Liu, 2016; M.J.

Lee et al., 2019; Shah et al., 2021). Understanding how better learning experiences can be shaped through hybrid learning remains an interesting and active research topic (Choi et al., 2021; M.J. Lee et al., 2019).

Asymmetric Impact of Hybrid Learning Attributes on Student Satisfaction

Course satisfaction is traditionally assessed by moti- vations, attitudes, and learning outcomes. Due to the advent of the COVID-19 pandemic, the context of learning has been transformed by necessity from conventional learning to online and hybrid learning.

Studies pertaining to course satisfaction in the current era tend to have shifted to include dimensions

(5)

outside the boundaries of conventional hospitality and tourism courses (e.g., online food and beverage labs; Orlowski et al., 2021). Although many education studies have examined the quality dimensions that affect student satisfaction (e.g., M.J. Lee et al., 2019;

Orlowski et al., 2021), a handful have been conducted from the perspective of hybrid learning. The tourism education literature has also neglected the impact of an asymmetrical analysis of programme quality on student satisfaction. For this reason, this research determined students’ overall satisfaction from the perspective of multidimensional quality attributes and took asymmetric impacts into account in the analysis.

According to Tonge and Moore (2007), traditional importance-performance analysis (IPA) should be reconsidered and substituted with importance- satisfaction analysis, which considers that satisfaction could better reflect customer attitude/response than performance. In addition, Mikulić and Prebežac (2008) asserted that using mean scores to divide attributes into different categories, such as high importance versus low importance, can lead to misleading implications, particularly when the mean values are relatively high (e.g., 6.5 out of 7.0). To address this concern and eval- uate the asymmetric effect of quality attributes on satisfaction, Mikulić and Prebežac (2008) proposed a new approach, as illustrated by impact range performance analysis (IRPA) and impact asymmetry analysis (IAA).

The concept behind these analyses is to examine performance attributes that affect customer satisfaction or dissatisfaction through the use of multiple regression methods in which various quality attributes are regressed on satisfaction. Significant attributes were then assigned to one of five categories: frustraters, dissatisfiers, hybrids, satisfiers, and delighters. Compared to the traditional IPA method, the impact range scores resulting from the standardized coefficients of regressions are more theoretically sound, and the outcomes are also more meaningful for industry professionals, considering that a number of research studies have validated the connection between quality and satisfaction.

Thus, this study adopted IRPA and IAA as the basis for the research analysis. This method is described in detail in the following section.

Similar to other types of tourism studies (see, for example, Fakfare & Wattanacharoensil, 2022 for low- carbon tourism, Lee and Choi, 2020 for shopping tourism, Lee et al., 2020 for honeymoon tourism; Ye et al., 2016 for OTA website quality; P. Wang et al., 2022; for small urban green space), the impacts of hybrid learning attributes on student satisfaction vary between attribute categories. According to Ju et al. (2019), the three-factor

framework (using dissatisfiers, hybrids, and satisfiers) has been popularly employed to explore asymmetric relationships in hospitality and tourism. To echo the distinctive characteristics of asymmetric impacts, Oliver (1997) proposed attributes as having a three- dimensional structure that forms customer perceptions.

Bivalent satisfiers (hybrid attributes) constitute satisfaction or dissatisfaction that is reliant on the degree of performance. Monovalent dissatisfiers (must-have attributes) produce dissatisfaction when the attributes are not in place. Nevertheless, these attributes do not generate satisfaction because customers take them for granted. Monovalent satisfiers (delighted and valued- added attributes) induce satisfaction when they are supplied. Individuals do not expect these attributes to be in place, so they do not generate dissatisfaction, even when not available. As with previous research, the current study implemented the following asymmetric constructs to explore the asymmetric nature of hybrid learning attributes:

(1) Hybrids refer to attributes that have a symmetric effect on satisfaction. If hybrid attributes are supplied, students are satisfied; if not, they feel unhappy.

(2) Satisfiers and delighters refer to positive asymmetrical attributes. Satisfiers are considered as attractive or extra attributes, as they are not expected to be supplied. Delighters generate satisfaction to a degree when students are highly joy- ful. However, delighters do not provoke student dissatisfaction if they are not available.

(3) Negative asymmetry belongs to attributes under dissatisfiers and frustraters. If dissatisfier attributes are not supplied, students are dissatisfied with the course. Frustraters are extreme dissatisfiers. Students would feel extremely dissatisfied if these attributes were not provided. Nevertheless, dissatisfiers and frustraters do not induce satisfaction, even if they are properly supplied.

Methodology

Measurement Development

Consistent with the item development procedure suggested by Hinkin (1995), the measures adopted in this study were extracted from a literature review, in-depth interviews, and an expert panel. These qualitative methods are important in identifying construct domains because the hybrid learning attributes are varied and inconsistently described in previous hospitality and tourism education literature. After considering the

(6)

extant hospitality and tourism education literature, an initial set of 30 items focused on hybrid learning attributes was first created. The items were derived by focus- ing on the hybrid learning environment, student support, innovative programme, industry involvement, programme reputation, and hybrid learning support dimensions (Bailey & Morais, 2005; Choi et al., 2021;

Gao et al., 2020; Li & Liu, 2016; M.J. Lee et al., 2019; Shah et al., 2021). Although hybrid learning attributes under the aforementioned constructs are vital to hospitality and tourism education in general, they have not been empirically developed and validated in the specific context of Thailand.

After the literature review, in-depth interviews were performed with three senior researchers whose research areas were relevant to hospitality and tourism education to examine whether there were any further concerns about hybrid learning during the COVID-19 pandemic. The first interviewee was a professor of tourism from a public university, and the other two interviewees were representatives from private universities in Thailand. The interviewees were asked to review the measures identified in the extant literature and suggest new items. As a result of this process, there were four new items concerning safety measures and protection: hygienic care and safety, procedures for preventing the spread of COVID-19, protocols for safety and health protection, and the provision of accident and COVID-19 insurance. As a result, 34 items were incorporated into a questionnaire and were next reviewed by a panel of two experts to assess face validity (DeVellis, 2003).

The panel experts were selected based on their valu- able experiences in teaching and curriculum development in Thailand. This study involved one lecturer who had more than 15 years of experience in teaching hospitality and tourism courses and one programme leader who had been involved in developing hospitality and tourism curricula in Thailand. The experts were asked to assess the applicability and representativeness of the measures identified in the earlier process. After evaluating the applicability of the items, the experts suggested minor improvements to enhance the clarity of the statements in the questionnaire. Considering the experts’ proficiency in hospitality and tourism education and the detailed information gained during this process (Morse, 2000), the content and face validity of the measures were deemed appropriate. In addition, course satisfaction was measured with four items mod- ified from Sun et al. (2008). A Likert scale ranging from 1 (“strongly disagree”) to 6 (“strongly agree”) was uti- lized to measure hybrid learning attributes and satisfaction.

Data Collection

Given that a field survey was not advisable during the COVID-19 pandemic (Wattanacharoensil et al., 2022), a link to an online questionnaire was distributed in the last quarter of 2021 using purposive and snowball sampling methods. Professors at different universities that offered hybrid hospitality and tourism courses in Thailand were approached and asked to distribute the survey link to their students. The target population were undergraduate students who were (1) currently enrolled in a hospitality or tourism program in a university in Thailand and (2) had learning experiences with a hybrid learning classroom. As a consequence, 671 students par- ticipated in the survey. However, major missing values were found in 24 responses. Hence, 647 responses were kept for further statistical analysis (i.e., measurement validation and analysis of asymmetric relationships).

From the demographic profiles of the respondents, the undergraduate students were from seven different universities in Thailand, 53.3% of which were from a private university, and 47.7% were from public universities. Among the survey participants, 78% were female. Most of the students were currently in year 4 (60.4%), followed by year 3 (24.0%), year 2 (13.4%), and year 1 and others (2.2%).

Findings

Measurement Reliability and Validity

Considering the attributes of the hybrid learning dimensions previously verified in the qualitative procedures (i.e., an analysis of literature, in-depth interviews, and expert panel evaluation), the multi-dimensional attributes to measure the quality of hybrid learning classes were com- posed of seven constructs: hybrid learning environment, student support, innovative program, industry involvement, program reputation, hybrid learning support and safety measures, and protection. To confirm the measurement model validity, a confirmatory factor analysis (CFA) was conducted using the data from the Thai students (n = 647). Two items (availability of an online orientation program and the provision of training regarding technology usage) were in this process due to unsatisfactory factor loadings. As shown in Table 1, the results of CFA verified that the seven dimensions had adequate fit indices [χ2 = 1301.66 (df = 440), RMSEA = 0.055, CFI = 0.939, TLI = 0.931], thus indicating the satisfactory fit of the model to the data (Hair et al., 2010). The construct reliability of every dimension was acceptable, considering a minimum edge of 0.7 (Nunnally, 1978). The convergent and discriminant validities were supported given that the average variance extracted (AVE) scores were greater

(7)

than 0.5 and higher than the squared correlations of the investigated constructs in general (Fakfare & Lee, 2019;

Fornell & Larcker, 1981). In this study, the hybrid learning attributes were confirmed as comprising a seven- factor structure with 32 items.

Results of the Impact Asymmetry Analysis

To investigate the asymmetric impacts of hybrid learning attributes on satisfaction, this study implemented impact range performance analysis (IRPA) and impact asymmetry analysis (IAA). Following Mikulić and Prebežac’s (2008) suggestion, regressions of penalty and reward indices (PI and RI, respectively) were performed. Similar to other studies (e.g., Fakfare et al., 2021), the indices were set up with two dummy variables. The PI was created by specify- ing the lowest attribute performance scores. In this research, it was found that the lowest performance score of 1 (“strongly disagree”) fluctuated between 0.2% and 3.1% for all the hybrid learning attributes. Thus, given the acquiescent and extremely positive response styles of

Southeast Asian people who are likely to avoid negative responses (Harzing, 2006), this study coded the two lowest responses (1 = “strongly disagree” and 2 = “disagree”) as 1 in a dummy variable. The RI was generated in a similar way on the opposite end of the scale. The highest attribute performance responses (5 = “agree” and 6 = “strongly agree”) were also recoded as 1, while the other performance ratings were recoded as 0. These new dummy variables were then regressed on course satisfaction using average scores. While the RI represented an incremental increase in course satisfaction when the attribute performance score was high, the PI indicated an incremental decrease in satisfaction when the attribute performance score was low (Back, 2012). Next, the absolute values of the RI and PI were summed to obtain the range of impacts on satisfaction (RIS). Below are the equations that we used to calculate the satisfaction-generating potential (SGP) and dissatisfaction- generating potential (DGP) scores:

(a) SGPi = RI/RISi, (b) DGPi = PI /RISi and (c) IAi index = SGPi – DGPi

Table 1. Results of measurement validation (CFA).

Dimensions Factor Loading t-value

Dimension 1: Student support (SS) (AVE: 0.56, CR: 0.84)

SS1 Scholarships or financial support. 0.649 N/A

SS2 Online and onsite consultations for students. 0.787 16.684

SS3 Career services. 0.754 16.148

SS4 International exchange programs. 0.586 13.115

SS5 Faculty members specialized in student services. 0.803 16.935

Dimension 2: Hybrid learning support (HS) (AVE: 0.49, CR: 0.78)

HS1 The provision of digital tools for online learning e.g., tablet, laptop, internet, sim card. 0.712 N/A

HS2 Well-designed exercises/assignments to support hybrid learning. 0.663 15.693

HS3 The delivery of class materials e.g., food recipes, kitchen equipment and culinary materials for students to practice at home. 0.697 16.452

HS4 Consultation hours to support hybrid learning. 0.708 16.711

Dimension 3: Innovative curriculum (IN) (AVE: 0.69, CR: 0.90)

IN1 Hands-on learning experiences. 0.824 N/A

IN2 Opportunities for earning industry certifications. 0.825 24.723

IN3 Classes offered in different components of the hospitality industry. 0.826 25.235

IN4 Practical and theoretical hospitality courses. 0.849 25.862

Dimension 4: Industry involvement (NT) (AVE: 0.70, CR: 0.90)

NT1 Student organizations that target the hospitality industry. 0.75 N/A

NT2 Required work experience as a part of the study program. 0.83 22.158

NT3 Diverse employment opportunities. 0.804 21.372

NT4 Networking opportunities on and off campus. 0.823 21.952

NT5 Opportunities for interactions with industry people. 0.828 22.094

Dimension 5: Hybrid learning environment (HL) (AVE: 0.50, CR: 0.88)

HL1 Visually appealing campus environment. 0.605 N/A

HL2 Live demonstration facilities. 0.722 15.111

HL3 Courses provided in diverse delivery formats (hybrid, online). 0.596 13.066

HL4 Computer laboratories/study areas. 0.75 15.514

HL5 Tutoring services. 0.807 16.324

HL6 Adequate student-to-faculty ratio. 0.742 15.407

HL7 Suitability of online learning environment. 0.715 15.007

Dimension 6: Program reputation (RC) (AVE: 0.48, CR: 0.72)

RC1 Program reputation. 0.698 N/A

RC2 Faculty with significant academic reputation. 0.555 15.74

RC3 Faculty members with substantial industry experiences. 0.774 18.885

Dimension 7: Safety measures and protection (SF) (AVE: 0.68, CR: 0.90)

SF1 Adequate procedures of hygienic care and safety when taking an online/on-campus class. 0.814 N/A

SF2 Adequate procedures for preventing the spread of COVID-19. 0.851 25.369

SF3 Protocols for safety and health protection are properly communicated. 0.86 25.745

SF4 The university’s provision of accident and COVID-19 insurance. 0.777 20.001

Note: Maximum likelihood estimation was employed. Hence, t-values are not obtained (N/A).

(8)

As proposed by Mikulić and Prebežac (2008), impact asymmetry (IA) can be implemented to organize quality attributes into different categories (delighters, satisfiers, hybrids, dissatisfiers, and frustrators). Especially, when the SGP is greater than the DGP, a quality attribute is deemed a satisfier because it evokes more pleasure than displeasure. In contrast, when the DGP is higher than the SGP, a quality attribute is considered a dissatisfier, as customers realize more dissatisfaction than satisfaction (Lee et al., 2020). A hybrid attribute can be observed when the arithmetic difference between the SGP and DGP is small, implying that students tend to perceive identical effects in terms of satisfaction and dissatisfaction. Delighters are extreme satisfiers, while frustraters are extreme dissatisfiers. Given the threshold of the IA, this research developed the following range, as recommended by Mikulić and Prebežac (2008), to classify the hybrid learning attributes into five different asymmetric zones: (1) delighters (IA > 0.6), (2) satisfiers (0.1 < IA ≤

0.6), (3) hybrids (−0.1 ≤ IA ≤ 0.1), (4) dissatisfiers (−0.6

≤ IA < −0.1), and (5) frustraters (IA ≤ −0.6).

Table 2 shows the IAA findings. Based on the IAA results, we can see different attribute types in each dimension. For example, student support, financial support, and the availability of international exchange programs were identified as dissatisfiers. Consultation services was identified as a satisfier, and career services was considered a frustrater. In innovative curriculum, hands-on learning experiences, opportunities for earning industry certifications, and a wide variety of classes in different components of the industry were categorized as satisfiers, and practical/theoretical course was considered a delighter. Dissatisfiers were dominant in safety measures and protection, while satisfiers were mostly found in program reputation and hybrid learning environment.

Furthermore, Figure 1 (the IRPA grid) was drawn to show the simultaneous assessment of the RIS (X-axis)

Table 2. Results of IRPA and IAA.

Hybrid learning attributes RI API RIS SGP DGP IA

Asymmetric Range Student support (SS)

SS1 Scholarships or financial support. .019 −0.06 0.08 0.23 0.77 −0.54 Dissatisfier

SS2 Online and onsite consultations for students. .053 −0.03 0.08 0.68 0.32 0.36 Satisfier

SS3 Career services. .009 −0.05 0.05 0.16 0.84 −0.67 Frustrater

SS4 International exchange programs. .021 0.05 0.07 0.29 0.71 −0.41 Dissatisfier

SS5 Faculty members specialized in student services. .057 −0.06 0.12 0.49 0.51 −0.02 Hybrid Hybrid learning support (HS)

HS1 The provision of digital tools for online learning e.g., tablet, laptop, internet, sim card. 0.08 0.01 0.10 0.85 0.15 0.69 Delighter HS2 Well-designed exercises/assignments to support hybrid learning. 0.04 −0.16 0.20 0.19 0.81 −0.62 Frustrater HS3 The delivery of class materials e.g., food recipes, kitchen equipment and culinary materials

for students to practice at home.

0.10 −0.07 0.17 0.58 0.42 0.15 Satisfier

HS4 Consultation hours to support hybrid learning. 0.25 −0.05 0.30 0.84 0.16 0.67 Delighter

Innovative curriculum (IN)

IN1 Hands-on learning experiences. 0.19 −0.09 0.28 0.67 0.33 0.33 Satisfier

IN2 Opportunities for earning industry certifications. 0.15 −0.04 0.20 0.78 0.22 0.56 Satisfier IN3 Classes offered in different components of the hospitality industry. 0.17 −0.07 0.24 0.71 0.29 0.42 Satisfier

IN4 Practical and theoretical hospitality courses. 0.17 −0.02 0.19 0.90 0.10 0.80 Delighter

Industry involvement (NT)

NT1 Student organizations that target the hospitality industry. 0.12 −0.12 0.24 0.50 0.50 −0.01 Hybrid NT2 Required work experience as a part of the study program. 0.05 −0.07 0.12 0.44 0.56 −0.13 Dissatisfier

NT3 Diverse employment opportunities. 0.00 0.01 0.01 −0.39 1.39 −1.77 Frustrater

NT4 Networking opportunities on and off campus. 0.02 −0.04 0.03 −0.61 1.61 −2.22 Frustrater

NT5 Opportunities for interactions with industry people. 0.07 0.02 0.09 0.75 0.25 0.50 Satisfier Hybrid learning environment (HL)

HL1 Visually appealing campus environment. .200 −.076 0.28 0.72 0.28 0.45 Satisfier

HL2 Live demonstration facilities. .184 −.017 0.20 0.92 0.08 0.83 Delighter

HL3 Courses provided in diverse delivery formats (hybrid, online). .258 −.107 0.37 0.71 0.29 0.41 Satisfier

HL4 Computer laboratories/study areas. .037 −.022 0.06 0.63 0.37 0.26 Satisfier

HL5 Tutoring services. .043 −.049 0.09 0.47 0.53 −0.06 Hybrid

HL6 Adequate student-to-faculty ratio. .057 .009 0.07 0.86 0.14 0.72 Delighter

HL7 Suitability of online learning environment. .027 −.131 0.16 0.17 0.83 −0.66 Frustrater

Program reputation (RC)

RC1 Program reputation. .103 −.081 0.18 0.56 0.44 0.12 Satisfier

RC2 Faculty with significant academic reputation. .199 −.111 0.31 0.64 0.36 0.28 Satisfier

RC3 Faculty members with substantial industry experiences. .045 .049 0.09 0.48 0.52 −0.04 Hybrid Safety measures and protection (SF)

SF1 Adequate procedures of hygienic care and safety when taking an online/on-campus class. .071 −.109 0.18 0.39 0.61 −0.21 Dissatisfier SF2 Adequate procedures for preventing the spread of COVID-19. .005 .013 0.02 0.26 0.74 −0.47 Dissatisfier SF3 Protocols for safety and health protection are properly communicated. .070 −.022 0.09 0.76 0.24 0.52 Satisfier SF4 The university’s provision of accident and COVID-19 insurance. .023 −.051 0.07 0.31 0.69 −0.38 Dissatisfier Note: RI = reward index, PI = penalty index, RIS = the range of impacts on satisfaction, SGP = satisfaction-generating potential, DGP = dissatisfaction-generating

potential, IA = impact asymmetry

(9)

Figure 1. IRPA grid.

(10)

and IA (Y-axis). This analysis can help in gaining a comprehensive understanding of the identified hybrid learning attributes. The major points to discuss are attributes with similar/greater RISs and lower IAAs.

For instance, under the student support dimension, attributes 1 and 2 (dissatisfier and satisfier, respectively) have identical RIS scores but contrasting asymmetric effects. Further discussions of simultaneous judgment are illustrated in the practical implications section.

Discussion and Implications Theoretical Implication

To validate the underlying attributes of hybrid learning and explore its asymmetric impact on course satisfaction, both qualitative and quantitative approaches were employed in this study. The results add insightful knowledge to the hospitality and tourism education literature.

This research first consisted of a comprehensive analysis of the literature, in-depth interviews, and an expert panel review, followed by measurement validation utilizing data from an online survey to verify the hybrid learning quality attributes. As a result, a seven-dimension structure of hybrid learning attributes was revealed, consisting of a hybrid learning environment, student support, innovative programme, industry involvement, programme reputation, hybrid learning support and safety measures, and protection. Although previous research used quality attributes to explore hospitality and tourism education phe- nomena, prior studies (e.g., Choi et al., 2021; M.J. Lee et al., 2019) employed attributes from the literature and implemented them based on diverse dimensions. No prior research has verified the dimensions/attributes of hybrid learning while considering issues pertaining to the emergence of COVID-19. Following a rigorous process of verifying hybrid learning attributes (Hinkin, 1995), this study detected domains such as hybrid learning support and safety measures and protection that had not been described in the previous literature. By taking both onsite and online classroom environments into account, the identified quality attributes suitably reflect key hybrid learning attributes. The findings of this research contri- bute to the extant hospitality and tourism education literature in various ways. In particular, the verified measures can be helpful in facilitating future hospitality and tourism education studies.

This research also investigated the dynamic effects of hybrid learning attributes on student satisfaction. As with previous research (e.g., Lee et al., 2020; Fakfare et al., 2021), IRPA and IAA were employed. Prior studies have generally adopted a symmetric linear relationship to explore whether the predictors affect outcomes in

a negative/positive direction. If the results from these studies revealed non-significant relationships, attributes were explained as not influencing satisfaction; however, the asymmetric impact was not considered. As claimed by Ju et al. (2019), a comprehensive insight into asymmetric impact allows scholars and practitioners to understand the asymmetric relationships between variables that symmetric relationships cannot explain. In addition, Lei and So (2021) encouraged further studies using an innovative research design/approach to capture unexplored aspects that affect student satisfaction with hybrid learning. In this study, an analysis of asymmetry through IRPA and IAA permitted us to identify a three- factor model of hybrid learning. For example, in Table 2, the 11 attributes under the dimensions of student support, hybrid learning support, industry involvement, hybrid learning environment and safety measures, and protection were found to be must-have attributes (dissatisfiers or frustraters) that exhibited negative asymmetric impacts. The current study expected that the attributes under the dimensions of student and learning support (e.g., scholarships, provision of career services, international exchange programmes, and well-designed assignments), industry involvement (e.g., work experience, employment opportunities, and networking opportunities), hybrid learning environment (e.g., suitability of online learning), and safety measures and protection (e.g., adequate procedures of hygienic care and the provision of COVID-19 insurance) would be taken for granted by students. These attribute types would lead to dissatisfaction if not supplied or well managed. However, students do not necessarily feel high satisfaction, even if the attributes are offered.

Given that student support services and measures for health are a high concern during a pandemic (Choi et al., 2021; Gao et al., 2020; Li & Liu, 2016; M.J. Lee et al., 2019; Shah et al., 2021), these findings are reasonable and understandable.

In addition to the value-added or delight attributes (e.g., the provision of digital tools for online learning, live demonstration facilities, adequate student-to-faculty ratio, and provision of theoretical hospitality courses), several attributes were identified as hybrids (e.g., faculty members specialized in student services, student organizations that target the hospitality industry, tutoring services, and faculty members with substantial industry experiences). The results suggest that students are either happy or displeased, depending on the performance of the hybrid attributes. Considering the above-mentioned analysis, it can be observed that the dynamic characteristics of hybrid learning cannot be recognized when a symmetric effect is analyzed. Therefore, by implement- ing IRPA and IAA, the present work provides results not

(11)

identified in the existing hospitality and tourism education literature and complements this literature by recog- nizing the differential impact of hybrid learning attributes on course satisfaction.

Practical Implications

An identification of the differential impacts of hybrid learning attributes offers hospitality and tourism programme directors, university administrators, and instructors insight into how to prioritize attributes in a way that increases the enjoyment of learning by students. Based on a three-factor model, this study categorized hybrid learning quality into must-have, hybrid, and value-added attributes (Figure 2). Must-have attributes are essential given that students have a high demand for these elements. This work discovered must-have attributes of hybrid learning quality, such as the availability of scholarships or financial support, international exchange programmes, internships, and safety measures and protection (e.g., hygienic care and safety and the provision of accident and COVID- 19 insurance). Some attributes were commonly found to be vitally important in earlier hospitality and tourism education studies, such as the attributes of the availability of financial aid and career services (M.J. Lee et al., 2019).

Students perceived the performance quality of must-have attributes as very sensitive. According to Park and Jones (2021), one of the important requirements for students in taking a hybrid learning course is to have digital devices and internet access to facilitate their learning experience.

This may cause a challenge for some students who cannot

afford to buy suitable online learning tools. Considering the must-have attributes found in this research, programme directors and university administrators may consider providing scholarship opportunities for students.

The provision of scholarships not only benefits students in terms of monetary support for living expenses, but also facilitates their continuity of learning during a pandemic.

When must-have attributes are not arranged to meet students’ needs, the students can be extremely unhappy, albeit the presence of these elements does not necessarily generate the students’ satisfaction because must-have attributes can be taken for granted by students.

Among the must-have attributes identified in this research, career services, well-designed exercises/

assignments, diverse opportunities for employment, meeting industry people, and the suitability of an online learning environment are highly anticipated as frustraters by students. During a pandemic, course directors or university administrators should prioritize must-have qualities over value-added features to avoid disrupting students’ learning experiences. For example, programme directors may consider arranging virtual/

on-campus job fairs for students to learn about job opportunities in the field, given that students, particularly those in their senior year, are generally con- cerned with their future careers. Arranging a job fair would allow students to attend free workshops and seminars, which would provide them a chance to practise their interview skills, polish their resume, and network with multiple representatives from hospitality and tourism companies.

Figure 2. Prioritizing hybrid learning quality attributes.

(12)

Hybrid attributes are reflected in the presence of experts in student services, student clubs that connect with the industry, tutoring services, and faculty members with significant industry experiences. Value-added attributes are generally represented by attributes under programme reputation (e.g., faculty members with significant academic reputations), innovative curriculum (e.g., hands-on learning experiences and opportunities for earning industry certifications), learning environment (e.g., a visually appealing campus environment and live demonstration facilities), and hybrid learning support (e.g., the provision of digital tools for online learning, the delivery of class materials for students to practice at home, and consultation hours to support hybrid learning). Value-added attributes are those that are considered to delight and enthuse students.

However, these attributes do not necessarily provoke students’ dissatisfaction, even if they are not supplied.

For example, programme directors can go the extra mile by partnering with private companies or foundations to offer access to hardware, software, or high-speed con- nectivity for students (UNESCO, 2020). Students do not usually expect value-added attributes to be available.

In contrast, a hybrid attribute can induce students’

satisfaction/dissatisfaction depending on the attribute performance of programme quality. To avoid a dissatisfied learning experience, hospitality and tourism educators must prioritize hybrid over value-added elements by investing more effort and resources in developing hybrid attributes. Once the hybrid elements are properly supplied to meet the expectations of students, hospitality and tourism educators can further enhance the quality of value- added attributes. In this study, the provision of digital tools, offers of practical and theoretical hospitality courses, live demonstration facilities, and an adequate student-to- faculty ratio were shown to delight students.

This research verified hybrid learning attributes and categorized them in a three-factor model (must-have, hybrid, and value-added), which can be used as a recommendation of attribute prioritization. Hence, the results are especially useful for hospitality and tourism educators and programme directors who monitor the performance of hospitality and tourism education programmes. From this perspective, a periodic survey is necessary to gain a specific understanding of the quality of a hybrid learning course. The results of this research provide suggestions for educators regarding which attributes should be incorporated into a questionnaire and how to interpret the outcomes. For instance, when the results show a low performance of must-have attributes, a hospitality and tourism programme director should consider investing more effort into increasing the performance of these attributes, because must-have

attributes are critical to the success of a hybrid learning programme. As students take must-have attributes for granted, educators should only put effort into improving these attributes until their performance meets student expectations. Investing effort in providing must-have attributes that exceed expectations is unlikely to elicit student satisfaction.

In case survey findings indicate unsatisfying performance of delight and satisfier attributes, educators can expect an absence of student enjoyment in their course offerings. Education programme directors should then reevaluate and review value-added attributes with students to provide supplementary benefits, thus stimulat- ing delight and value perception. For example, before the emergence of COVID-19, the average student-to- faculty ratio for higher education in Thailand was found to be 20:1 (Crocco, 2018). Although modern technological platforms make it possible to provide the essence of lessons even when the student-to-faculty ratio is poor (Fassbender & Lucier, 2014), students would be delighted if university administrators or programme directors could maintain suitable student-to-instructor ratios when arranging hybrid learning classes.

According to Fulton (2012), an appropriate fit of learning content, academic rigor, and personal connections could be maintained when instructors spend sufficient time directly with students.

Another interesting attribute that delights students is the utilization of live demonstration facilities, such as kitchen and beverage labs. Although a university cannot fully provide face-to-face classes and activities for all its students during a pandemic, some classroom ground rules can be developed in accordance with the protocols suggested by health authorities as well as the procedures established by a university’s administration. Each hybrid classroom may allow 50%–75% of students on campus.

As physical distancing needs to be maintained, instructors can possibly divide students into sub-groups and create a class timetable that allows blended synchronous learning (UNICEF, 2021). From this perspective, technology can facilitate learning experiences during a pandemic and is considered an important element of disseminating knowledge and building practical skills (Fassbender & Lucier, 2014).

The simultaneous comparison of RIS and IA provides another interesting implication (see, Figure 1). The IRPA grids enable programme directors and university administrators to visually spot important elements that should be prioritized (i.e. high RISs and low IAs) while highlighting the attributes that students perceive as providing satisfaction and delight (i.e. high RISs and high IAs). Delighted or value-added attributes are those that excite students. Hybrid attributes with high RIS scores

(13)

are items that induce high satisfaction if properly offered and can lead to dissatisfaction if poorly managed.

The simultaneous observation of the RISs and IAs also revealed some attributes that have similar RIS values but contrasting IAs (e.g., scholarships, the arrangement of consultation hours, well-designed assignments, and the delivery of class materials for students to practice at home). Although these attributes may be well managed by programme directors or university administrators, they could affect the satisfaction of students differently. For example, scholarships and the arrangement of consultation hours have similar RIS values (0.08) but different asymmetric ranges (dissatisfier and satisfier, respectively). By overlooking the asymmetric effect of these attributes, programme directors and university administrators may receive misleading information when developing and designing hybrid learning courses for hospitality and tourism students.

Moreover, specific attention should be given to must-have attributes (i.e. hybrid learning attributes that have a considerable effect on dissatisfaction). As illustrated in Figure 1, dissatisfiers or frustraters with significant RISs are (1) well-designed assignments to support hybrid learning, (2) required work experience as a part of the study programme, (3) career services, (4) scholarships, (5) international exchange programmes, (6) diverse employment opportunities, (7) networking opportunities, (8) suitability of online learning environment, (9) adequate procedures of hygienic care and safety, (10) adequate procedures for preventing the spread of disease, and (11) the provision of accident and health insurance. The programme directors and university administrators should direct a particular focus on these attributes, given that they could exert an unfavorable impact on student learning experience/satisfaction if not properly offered (Mikulić & Prebežac, 2008).

Limitations and Future Research

Similar to other studies, this research is not without limitations. First, although this study provides in-depth details to widen the knowledge of hybrid learning quality attributes, the results are mainly based on hospitality and tourism courses offered in Thailand. The findings may only reflect this particular context. Thus, research performed in different countries/regions could help expand knowledge about hospitality and tourism hybrid courses by either confirming the results or showing differences based on other contexts. Second, a different coding system was applied to create the penalty dummy variables. In other studies (e.g., Lee et al., 2020), a performance score of 1 was coded as 1. Nevertheless,

the coding scheme applied in this study (i.e. coding the two lowest levels of responses as 1) was used in several research studies that employed dummy regression on satisfaction (Ye et al., 2016).

Another limitation concerns the ability of IRPA and IAA to obtain relative performance values of hybrid learning quality on student satisfaction. IRPA and IAA have been employed to prioritize attributes in several tourism studies (e.g., Lee et al., 2020; Fakfare et al., 2021). Because the impact of attributes on student satisfaction is assessed using only the high and low values of attribute performance, the non-linearity of attribute impact on student satisfaction may not be fully uncovered. In addition, these analytical procedures can be employed only to assess hybrid learning attributes at the attribute level, while the asymmetric effects between the learning dimensions and student satisfaction were not considered. Future scholars are recommended to undertake additional approaches (e.g., impact-asymmetry analysis) that can discover the asymmetric impact of quality attributes on satisfaction at both the dimension and attribute levels (Seric & Mikulic, 2020) and other unexplored relationships. Finally, the results of this study generally relied on cross-sectional data with self-reported measures.

As Bland (2001) asserted, cross-sectional data may cause bias, such that the findings may vary depending on the survey period and time. Future studies can perform longitudinal research to assess student’s perception/satisfaction of hybrid learning attributes after the end of the COVID-19 pandemic.

Disclosure Statement

No potential conflict of interest was reported by the author(s).

Funding

This work was supported by the Faculty of Business Administration and Accountancy, Khon Kaen University (Thailand).

ORCID

Supawat Meeprom, PhD http://orcid.org/0000-0003-0263- 4616

Pipatpong Fakfare, D.HTM http://orcid.org/0000-0003- 3446-384X

References

Ali, F., Nair, P. K., & Hussain, K. (2016). An assessment of students’ acceptance and usage of computer supported collaborative classrooms in hospitality and tourism schools.

(14)

Journal of Hospitality, Leisure, Sport & Tourism Education, 18, 51–60. https://doi.org/10.1016/j.jhlste.2016.03.002 Back, K. J. (2012). Impact-range performance analysis and

asymmetry analysis for improving quality of Korean food attributes. International Journal of Hospitality Management, 31(2), 535–543. https://doi.org/10.1016/j.ijhm.2011.07.013 Bailey, K. D., & Morais, D. B. (2005). Exploring the use of

blended learning in tourism education. Journal of Teaching in Travel & Tourism, 4(4), 23–36. https://doi.org/10.1300/

J172v04n04_02

Baker, M. A. (2021). Educational distancing: A mixed-methods study of student perceptions in the time of coronavirus.

Journal of Hospitality & Tourism Education, 33(3), 207–221.

https://doi.org/10.1080/10963758.2021.1907194

Baker, M. A., & Magnini, V. P. (2016). The evolution of services marketing, hospitality marketing and building the constituency model for hospitality marketing. International Journal of Contemporary Hospitality Management, 28(8), 1510–1534. https://doi.org/10.1108/IJCHM-01-2015-0015 Bangkok Post. (2022). New Covid-19 measures for schools

nationwide. https://www.bangkokpost.com/thailand/gen eral/2241899/new-covid-19-guidelines-for-schools- childrens-day-activities-postponed

Bland, M. (2001). An introduction to medical statistics (3rd ed.). Oxford University.

Cheng, M. T., & Agyeiwaah, E. (2021). Exploring Chinese students’ issues and concerns of studying abroad amid COVID-19 pandemic: An actor-network perspective.

Journal of Hospitality, Leisure, Sport & Tourism Education, 100349. https://doi.org/10.1016/j.jhlste.2021.100349 Choi, J. J., Robb, C. A., Mifli, M., & Zainuddin, Z. (2021).

University students’ perception to online class delivery methods during the COVID-19 pandemic: A focus on hospitality education in Korea and Malaysia. Journal of Hospitality, Leisure, Sport & Tourism Education, 29, 100336. https://doi.org/10.1016/j.jhlste.2021.100336 Crocco, O. S. (2018). Thai higher education: Privatization and

massification. In G. Fry (Ed.), Education in Thailand.

Education in the Asia-Pacific region: Issues, concerns and prospects (Vol. 42, pp. 223–255). Springer. https://doi.org/

10.1007/978-981-10-7857-6_9

DeVellis, R. F. (2003). Scale development: Theory and applica- tions (2nd ed.). Sage.

Fakfare, P., & Lee, J. S. (2019). Developing and validating a scale for multidimensional attributes of honeymoon tourism. Journal of Hospitality & Tourism Research, 43(8), 1199–1224. https://doi.org/10.1177/1096348019850279 Fakfare, P., Lee, J. S., & Han, H. (2022). Thailand tourism:

A systematic review. Journal of Travel & Tourism Marketing, 39(2), 188–214. https://doi.org/10.1080/

10548408.2022.2061674

Fakfare, P., Lee, J. S., & Ryu, K. (2020b). Examining honeymoon tourist behavior: Multidimensional quality, fantasy, and destination relational value. Journal of Travel &

Tourism Marketing, 37(7), 836–853. https://doi.org/10.

1080/10548408.2020.1835786

Fakfare, P., Talawanich, S., & Wattanacharoensil, W. (2020a).

A scale development and validation on domestic tourists’

motivation: The case of second-tier tourism destinations.

Asia Pacific Journal of Tourism Research, 25(5), 489–504.

https://doi.org/10.1080/10941665.2020.1745855

Fakfare, P., & Wattanacharoensil, W. (2022). Low-carbon tourism: Determining domestic tourist perception from Thailand: TOURISM AGENDA 2030. Tourism Review.

https://doi.org/10.1108/TR-12-2021-0537

Fakfare, P., Wattanacharoensil, W., & Graham, A. (2021).

Exploring multi-quality attributes of airports and the asymmetric effects on air traveller satisfaction: The case of Thai international airports. Research in Transportation Business

& Management, 41, 100648. https://doi.org/10.1016/j.rtbm.

2021.100648

Fassbender, W., & Lucier, J. (2014). Equalizing the teacher-to- student ratio through technology: A new perspective on the role of blended learning. Voices from the Middle, 22(2), 21–28.

Fornell, C., & Larcker, D. (1981). Evaluating structural equa- tion models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50. https://

doi.org/10.1177/002224378101800104

Fulton, K. (2012). Upside Down and Inside Out: Flip Your Classroom to Improve Student Learning. Learning &

Leading with Technology, 39, 12–17.

Gao, B. W., Jiang, J., & Tan, Y. (2020). The effect of blended learning platform and engagement on students’ satisfaction- the case from the tourism management teaching.

Journal of Hospitality, Leisure, Sport & Tourism Education, 27, 100272. https://doi.org/10.1016/j.jhlste.2020.100272 Griffin, W. C. (2022). Perceptions of hospitality industry pro-

fessionals and hospitality faculty on industry-academia collaborations. Journal of Hospitality & Tourism Education, 34(2), 99–110. https://doi.org/10.1080/

10963758.2020.1791137

Hair, J. F., Black, W., Babin, B. J., & Anderson, R. (2010).

Multivariate data analysis (7th ed.). Prentice Hall/Pearson.

Harzing, A. W. (2006). Response styles in cross-national survey research: A 26-country study. International Journal of Cross Cultural Management, 6(2), 243–266. https://doi.org/

10.1177/1470595806066332

Hinkin, T. (1995). A review of scale development practices in the study of organizations. Journal of Management, 21(5), 967–988. https://doi.org/10.1177/014920639502100509 Horng, J. S., Hsu, H., & Tsai, C. Y. (2019). Learning corporate

ethics and social responsibility: Developing an influential curriculum for undergraduate tourism and hospitality students. Journal of Hospitality, Leisure, Sport & Tourism Education, 24, 100–109. https://doi.org/10.1016/j.jhlste.

2019.01.003

Hsu, C. H. (2018). Tourism education on and beyond the horizon. Tourism Management Perspectives, 25, 181–183.

https://doi.org/10.1016/j.tmp.2017.11.022

Jiang, L., & Aexakis, G. (2017). Comparing students’ and man- agers’ perceptions of essential entry-level management com- petencies in the hospitality industry: An empirical study.

Journal of Hospitality, Leisure, Sport & Tourism Education, 20, 32–46. https://doi.org/10.1016/j.jhlste.2017.01.001 Ju, Y., Back, K. J., Choi, Y., & Lee, J. S. (2019). Exploring

Airbnb service quality attributes and their asymmetric effects on customer satisfaction. International Journal of Hospitality Management, 77, 342–352. https://doi.org/10.

1016/j.ijhm.2018.07.014

Lee, J. S., & Choi, M. (2020). Examining the asymmetric effect of multi-shopping tourism attributes on overall shopping